This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.
Testing the association between 17261 genes and 5 clinical features across 45 samples, statistically thresholded by Q value < 0.05, no clinical feature related to at least one genes.
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No genes correlated to 'Time to Death', 'AGE', 'GENDER', 'KARNOFSKY.PERFORMANCE.SCORE', and 'RADIATIONS.RADIATION.REGIMENINDICATION'.
Complete statistical result table is provided in Supplement Table 1
Table 1. Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at Q value < 0.05.
Clinical feature | Statistical test | Significant genes | Associated with | Associated with | ||
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Time to Death | Cox regression test | N=0 | ||||
AGE | Spearman correlation test | N=0 | ||||
GENDER | t test | N=0 | ||||
KARNOFSKY PERFORMANCE SCORE | Spearman correlation test | N=0 | ||||
RADIATIONS RADIATION REGIMENINDICATION | t test | N=0 |
Table S1. Basic characteristics of clinical feature: 'Time to Death'
Time to Death | Duration (Months) | 1-47.9 (median=6.7) |
censored | N = 22 | |
death | N = 23 | |
Significant markers | N = 0 |
Table S2. Basic characteristics of clinical feature: 'AGE'
AGE | Mean (SD) | 62.49 (13) |
Significant markers | N = 0 |
Table S3. Basic characteristics of clinical feature: 'GENDER'
GENDER | Labels | N |
FEMALE | 20 | |
MALE | 25 | |
Significant markers | N = 0 |
No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.
Table S4. Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'
KARNOFSKY.PERFORMANCE.SCORE | Mean (SD) | 76.97 (13) |
Significant markers | N = 0 |
No gene related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
Table S5. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'
RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N |
NO | 29 | |
YES | 16 | |
Significant markers | N = 0 |
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Expresson data file = GBM-TP.meth.for_correlation.filtered_data.txt
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Clinical data file = GBM-TP.clin.merged.picked.txt
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Number of patients = 45
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Number of genes = 17261
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Number of clinical features = 5
For survival clinical features, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels
For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R
For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R
For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.